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Evolving AVX512 Parallel C Code Using GP

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Genetic Programming (EuroGP 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11451))

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Abstract

Using 512 bit Advanced Vector Extensions, previous development history and Intel documentation, BNF grammar based genetic improvement automatically ports RNAfold to AVX, giving up to a 1.77 fold speed up. The evolved code pull request is an accepted GI software maintenance update to bioinformatics package ViennaRNA.

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References

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Acknowledgements

Funded by EPSRC grant EP/M025853/1.

GP code will be available via the author’s home page.

Author information

Authors and Affiliations

  1. Computer Science, CREST, UCL, London, WC1E 6BT, UK

    William B. Langdon

  2. Institute for Theoretical Chemistry, University of Vienna, 1090, Vienna, Austria

    Ronny Lorenz

Authors
  1. William B. Langdon
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  2. Ronny Lorenz
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Corresponding author

Correspondence to William B. Langdon .

Editor information

Editors and Affiliations

  1. Brno University of Technology, Brno, Czech Republic

    Lukas Sekanina

  2. Memorial University, St. John's, NL, Canada

    Ting Hu

  3. University of Coimbra, Coimbra, Portugal

    Nuno Lourenço

  4. HTWK Leipzig University of Applied Sciences, Leipzig, Germany

    Hendrik Richter

  5. University of Granada, Granada, Spain

    Pablo García-Sánchez

Appendix

Appendix

Fig. 9.
figure 9

Starting point for evolution. C code derived from ViennaRNA (Figs. 2 and 3).Pairs of lines of code were manually added before the for loops to provide feed stock for evolution [2] but appear not to have been helpful. Instead successful changes (Fig. 4) come from the for loops themsleves.

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Langdon, W.B., Lorenz, R. (2019). Evolving AVX512 Parallel C Code Using GP. In: Sekanina, L., Hu, T., Lourenço, N., Richter, H., García-Sánchez, P. (eds) Genetic Programming. EuroGP 2019. Lecture Notes in Computer Science(), vol 11451. Springer, Cham. https://doi.org/10.1007/978-3-030-16670-0_16

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  • DOI: https://doi.org/10.1007/978-3-030-16670-0_16

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